
RoleAware Modeling for Nary Relational Knowledge Bases
Nary relational knowledge bases (KBs) represent knowledge with binary a...
read it

Search to aggregate neighborhood for graph neural network
Recent years have witnessed the popularity and success of graph neural n...
read it

Tensorizing Subgraph Search in the Supernet
Recently, a special kind of graph, i.e., supernet, which allows two node...
read it

Decoupling Representation and Classifier for Noisy Label Learning
Since convolutional neural networks (ConvNets) can easily memorize noisy...
read it

A Survey of Labelnoise Representation Learning: Past, Present and Future
Classical machine learning implicitly assumes that labels of the trainin...
read it

Graph Neural Network with Automorphic Equivalence Filters
Graph neural network (GNN) has recently been established as an effective...
read it

Nonlocal Meets Global: An Iterative Paradigm for Hyperspectral Image Restoration
Nonlocal lowrank tensor approximation has been developed as a stateof...
read it

Efficient, Simple and Automated Negative Sampling for Knowledge Graph Embedding
Negative sampling, which samples negative triplets from nonobserved one...
read it

Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering
Negative sampling approaches are prevalent in implicit collaborative fil...
read it

Simplifying Architecture Search for Graph Neural Network
Recent years have witnessed the popularity of Graph Neural Networks (GNN...
read it

Efficient LowRank Matrix Learning by Factorizable Nonconvex Regularization
Matrix learning is at the core of many machine learning problems. To enc...
read it

Generalizing Tensor Decomposition for Nary Relational Knowledge Bases
With the rapid development of knowledge bases (KBs), link prediction tas...
read it

Efficient Backbone Search for Scene Text Recognition
Scene text recognition (STR) is very challenging due to the diversity of...
read it

Neural Recurrent Structure Search for Knowledge Graph Embedding
Knowledge graph (KG) embedding is a fundamental problem in mining relati...
read it

Searching to Exploit Memorization Effect in Learning from Corrupted Labels
Sampleselection approaches, which attempt to pick up clean instances fr...
read it

Searching for Interaction Functions in Collaborative Filtering
Interaction function (IFC), which captures interactions among items and ...
read it

Differentiable Neural Architecture Search via Proximal Iterations
Neural architecture search (NAS) recently attracts much research attenti...
read it

Robust Learning from Noisy Sideinformation by Semidefinite Programming
Robustness recently becomes one of the major concerns among machine lear...
read it

AutoKGE: Searching Scoring Functions for Knowledge Graph Embedding
Knowledge graph embedding (KGE) aims to find low dimensional vector repr...
read it

Fewshot Learning: A Survey
The quest of `can machines think' and `can machines do what human do' ar...
read it

NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding
Knowledge Graph (KG) embedding is a fundamental problem in data mining r...
read it

Nonlocal Meets Global: An Integrated Paradigm for Hyperspectral Denoising
Nonlocal lowrank tensor approximation has been developed as a stateof...
read it

Privacypreserving Transfer Learning for Knowledge Sharing
In many practical machinelearning applications, it is critical to allow...
read it

Scalable Tensor Completion with Nonconvex Regularization
Lowrank tensor completion problem aims to recover a tensor from limited...
read it

Online Convolutional Sparse Coding with SampleDependent Dictionary
Convolutional sparse coding (CSC) has been popularly used for the learni...
read it

Cosampling: Training Robust Networks for Extremely Noisy Supervision
Training robust deep networks is challenging under noisy labels. Current...
read it

Millionaire: A Hintguided Approach for Crowdsourcing
Modern machine learning is migrating to the era of complex models, which...
read it

Learning with Heterogeneous Side Information Fusion for Recommender Systems
Recommender System (RS) is a hot area where artificial intelligence (AI)...
read it

Scalable Robust Matrix Factorization with Nonconvex Loss
Robust matrix factorization (RMF), which uses the ℓ_1loss, often outper...
read it

Efficient Robust Matrix Factorization with Nonconvex Loss
Robust matrix factorization (RMF), which uses the ℓ_1loss, often outper...
read it

Efficient Robust Matrix Factorization with Nonconvex Penalties
Robust matrix factorization (RMF) is a fundamental tool with lots of app...
read it

LargeScale LowRank Matrix Learning with Nonconvex Regularizers
Lowrank modeling has many important applications in computer vision and...
read it

Scalable Online Convolutional Sparse Coding
Convolutional sparse coding (CSC) improves sparse coding by learning a s...
read it

Accelerated and Inexact SoftImpute for LargeScale Matrix and Tensor Completion
Matrix and tensor completion aim to recover a lowrank matrix / tensor f...
read it

Lossaware Binarization of Deep Networks
Deep neural network models, though very powerful and highly successful, ...
read it

Efficient Learning with a Family of Nonconvex Regularizers by Redistributing Nonconvexity
The use of convex regularizers allows for easy optimization, though they...
read it

Fast LowRank Matrix Learning with Nonconvex Regularization
Lowrank modeling has a lot of important applications in machine learnin...
read it
Quanming Yao
verfied profile